000261736 001__ 261736
000261736 005__ 20190121181807.0
000261736 022__ $$a0018-9448
000261736 022__ $$a1557-9654
000261736 02470 $$a000422916500026$$2isi
000261736 0247_ $$a10.1109/TIT.2017.2782789$$2doi
000261736 037__ $$aARTICLE
000261736 245__ $$aProximity Operators of Discrete Information Divergences
000261736 260__ $$c2018$$aPiscataway$$bIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
000261736 269__ $$a2018-02-01
000261736 336__ $$aJournal Articles
000261736 520__ $$aWhile phi-divergences have been extensively studied in convex analysis, their use in optimization problems often remains challenging. In this regard, one of the main shortcomings of existing methods is that the minimization of phi-divergences is usually performed with respect to one of their arguments, possibly within alternating optimization techniques. In this paper, we overcome this limitation by deriving new closed-form expressions for the proximity operator of such two-variable functions. This makes it possible to employ standard proximal methods for efficiently solving a wide range of convex optimization problems involving phi-divergences. In addition, we show that these proximity operators are useful to compute the epigraphical projection of several functions. The proposed proximal tools are numerically validated in the context of optimal query execution within database management systems, where the problem of selectivity estimation plays a central role. Experiments are carried out on small to large scale scenarios.
000261736 650__ $$aComputer Science, Information Systems
000261736 650__ $$aEngineering, Electrical & Electronic
000261736 650__ $$aComputer Science
000261736 650__ $$aEngineering
000261736 6531_ $$aconvex optimization
000261736 6531_ $$adivergences
000261736 6531_ $$aproximity operator
000261736 6531_ $$aproximal algorithms
000261736 6531_ $$aepigraphical projection
000261736 6531_ $$acomposite monotone inclusions
000261736 6531_ $$af-divergence
000261736 6531_ $$aimage-reconstruction
000261736 6531_ $$amaximum-likelihood
000261736 6531_ $$adistance measures
000261736 6531_ $$aalpha-divergence
000261736 6531_ $$achannel capacity
000261736 6531_ $$ainverse problems
000261736 6531_ $$arate-distortion
000261736 6531_ $$amass-transfer
000261736 700__ $$0251490$$aEl Gheche, Mireille
000261736 700__ $$aChierchia, Giovanni
000261736 700__ $$aPesquet, Jean-Christophe
000261736 773__ $$k2$$tIeee Transactions On Information Theory$$q1092-1104$$j64
000261736 8560_ $$fpascal.frossard@epfl.ch
000261736 909C0 $$yApproved$$pLTS4$$xU10851$$mpascal.frossard@epfl.ch$$zMarselli, Béatrice$$0252393
000261736 909CO $$ooai:infoscience.epfl.ch:261736$$particle$$pSTI
000261736 961__ $$afantin.reichler@epfl.ch
000261736 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000261736 980__ $$aARTICLE
000261736 980__ $$aS2
000261736 980__ $$aWoS
000261736 981__ $$aoverwrite